class_docstr: Atari 2600 preprocessing wrapper.
  
  This class follows the guidelines in Machado et al. (2018),
  "Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents".
  
  Specifically, the following preprocess stages applies to the atari environment:
  - Noop Reset: Obtains the initial state by taking a random number of no-ops on reset, default max 30 no-ops.
  - Frame skipping: The number of frames skipped between steps, 4 by default
  - Max-pooling: Pools over the most recent two observations from the frame skips
  - Termination signal when a life is lost: When the agent losses a life during the environment, then the environment is terminated.
      Turned off by default. Not recommended by Machado et al. (2018).
  - Resize to a square image: Resizes the atari environment original observation shape from 210x180 to 84x84 by default
  - Grayscale observation: If the observation is colour or greyscale, by default, greyscale.
  - Scale observation: If to scale the observation between [0, 1) or [0, 255), by default, not scaled.
docstr: Make ale as a class property to avoid serialization error.
docstr_tok: ["Make","ale","as","a","class","property","to","avoid","serialization","error","."]
code: def ale(self):
      """Make ale as a class property to avoid serialization error."""
      return self.env.unwrapped.ale
  
file_path: gym/gym/wrappers/atari_preprocessing.py
imports: import numpy
  import gym
  from gym.spaces import Box
label_desc: Use image node_id 2 for calling the AtariPreprocessing obj's underlying member method code with example usage: obj.ale() and returns: self